Processors have become ubiquitous in modern society. Processors are found in many popularly used electronic devices such as, for example, personal computers, personal digital assistants, and cellular phones. Processors are also used in devices not thought of as traditionally being electronics, for example, automobiles and coffee makers. Processors used in today's most popular computers include software typically referred to as microcode. Microcode within a processor is implemented to achieve a defined set of assembly language instructions which are executed by the processor known as the processor's instruction set. A processor's instruction set and how the instruction set is used to achieve a certain result are referred to as the processor's instruction set architecture (“ISA”). The processor's ISA also necessarily describes much of the processor's internal architecture. The assembly language instructions of a processor's instruction set internally access data of a defined size commonly known as a word. The word size of a processor is defined by the processor's ISA. Earlier personal computers, for example, the IBM PC sold by International Business Machines of Armonk, N.Y. included a processor (the 8086) manufactured by Intel Corporation of Santa Clara, Calif. which had a word size of 16 bits. As the personal computer has evolved, processing power has increased by, among other things, increasing the word size of a processor. Increasing the word size allows a processor to process more data in a shorter amount of time. Many current personal computers implement 32 bit word ISAs, while future personal computers will be implementing 64 bit word ISAs. Larger computers such as mainframes have ISAs with larger word sizes while smaller devices such as hand held personal digital assistants and cellular telephones have smaller word sizes.
Mathematical computations which require vary large numbers, require high precision, and/or include complex mathematical equations are called floating-point calculations. When programming software, floating-point numbers are used when performing floating-point calculations. Floating-point numbers are often declared as “real” numbers in software. Floating-point numbers are commonly defined as having three parts: a sign, a significand (also known as a mantissa), and an exponent. Two well known standards set a framework for how floating-point numbers and calculations should be implemented—I.E.E.E. standard 754 (1985, reaffirmed 1990), the Standard for Binary Floating-Point Arithmetic; and I.E.E.E. standard 854 (1987), the Standard for Radix-Independent Floating-Point Arithmetic; available from the Institute of Electrical and Electronics Engineers, Inc., 445 Hoes Lane, Piscataway, N.J. 08855-1331 (collectively, I.E.E.E. Floating-Point Standards).
Floating-point support has been implemented in a number of ways with processors. In earlier personal computers, a floating-point co-processor was optionally available to be installed with and to assist a processor in handling floating-point calculations (e.g., Intel Corporation provided a Numeric Processor Extension chip named the 8087 to accompany the widely used 8086 processor). As personal computers have evolved, processors have incorporated floating-point capability within a processor by including one or more floating-point units in a processor. In addition, when floating-point capability is provided within a processor, memory internal to the processor is designated for use by and with floating-point units. Such memory is designated by the processor's architecture and ISA as the processor's floating-point registers. Floating-point registers are typically larger than other registers within the processor as they are designed to accommodate larger and/or more precise numbers by providing enough space for the sign, significand, and exponent of “real” numbers.
Traditionally, only specialized scientific and accounting application programs accessed a processor's floating-point capabilities. However, today, colorful graphic and multimedia images are in widespread use in, for example, internet web pages, architectural software applications, computer games, and animation creation programs. These images are stored in various compressed or encoded formats. The more detailed and higher resolution a graphical image is, the more floating-point calculations are needed to process (i.e., decompress or decode) and render the image on a computer monitor. As the use of graphic images has become popular and continues to grow, the use of a processor's floating-point mathematical capabilities has been increasing. Other factors such as use for audio processing are also contributing to an increased use of a processor's floating-point mathematical capabilities. To accommodate these and other needs, and to meet the ever growing demand for increased floating-point performance, the floating-point capability of processors is continually evolving.